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All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Massive neutrinos and degeneracies in Lyman-alpha forest simulations

Using a suite of hydrodynamical simulations with cold dark matter, baryons, and neutrinos, we present a detailed study of the effect of massive neutrinos on the 1-D and 3-D flux power spectra of the Lyman-α (Lyα) forest. The presence of massive neutrinos in cosmology induces a scale- and time-dependent suppression of structure formation that is strongest on small scales. Measuring this suppression is a key method for inferring neutrino masses from cosmological data, and is one of the main goals of ongoing and future surveys like eBOSS, DES, LSST, Euclid or DESI . The clustering in the Lyα forest traces the quasi-linear power at late times and on small scales. In combination with observations of the cosmic microwave background, the forest therefore provides some of the tightest constraints on the sum of the neutrino masses. However there is a well-known degeneracy between Σmν and the amplitude of perturbations in the linear matter power spectrum. We study the corresponding degeneracy in the 1-D flux power spectrum of the Lyα forest, and for the first time also study this degeneracy in the 3-D flux power spectrum. We show that the non-linear effects of massive neutrinos on the Lyα forest, beyond the effect of linear power amplitude suppression, are negligible, and this degeneracy persists in the Lyα forest observables to a high precision. Here, we discuss the implications of this degeneracy for choosing parametrisations of the Lyα forest for cosmological analysis.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Effective bias expansion for 21-cm cosmology in redshift space

A near-future detection of the 21-cm signal from the epoch of reionization will provide unique opportunities to probe the underlying cosmology, provided that such cosmological information can be extracted with precision. To this end, we further develop effective field theory (EFT) inspired techniques for the 21-cm brightness temperature field during the epoch of reionization, incorporating renormalized bias and a treatment of redshift space distortions. Notably, we confirm that in redshift space, measures of the 21-cm brightness, e.g., the power spectrum, should have irreducible contributions that lack a bias coefficient and therefore contain direct, astrophysics-free information about the cosmological density field; in this work, we study this effect beyond linear order. To validate our theoretical treatment, we fit the predicted EFT Fourier-space shapes to the thesan suite of hydrodynamical simulations of reionization at the field level, where the considerable number of modes prevents overfitting. We find agreement at the level of a few percent between the 21-cm power spectrum from the EFT fits and simulations over the wave number range k ≲ 0.8 h/Mpc and neutral fraction x HI ≳ 0.4, which is imminently measurable by the Hydrogen Epoch of Reionization Array and future experiments. Furthermore, the ability of the EFT to describe the 21-cm signal extends to simulations that have different astrophysical prescriptions for reionization as well as simulations with interacting dark matter.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Indra: a public computationally accessible suite of cosmological N -body simulations

ABSTRACT Indra is a suite of large-volume cosmological N-body simulations with the goal of providing excellent statistics of the large-scale features of the distribution of dark matter. Each of the 384 simulations is computed with the same cosmological parameters and different initial phases, with 10243 dark matter particles in a box of length 1 h−1 Gpc, 64 snapshots of particle data and halo catalogues, and 505 time-steps of the Fourier modes of the density field, amounting to almost a petabyte of data. All of the Indra data are immediately available for analysis via the SciServer science platform, which provides interactive and batch computing modes, personal data storage, and other hosted data sets such as the Millennium simulations and many astronomical surveys. We present the Indra simulations, describe the data products and how to access them, and measure ensemble averages, variances, and covariances of the matter power spectrum, the matter correlation function, and the halo mass function to demonstrate the types of computations that Indra enables. We hope that Indra will be both a resource for large-scale structure research and a demonstration of how to make very large data sets public and computationally accessible.

Falck, Bridget↗
DOE OSTI2024

Solar reflection of dark matter with dark-photon mediators

Abstract We consider the scattering of low-mass halo dark-matter particles in the hot plasma of the Sun, focusing on dark matter that interact with ordinary matter through a dark-photon mediator. The resulting “solar-reflected” dark matter (SRDM) component contains high-velocity particles, which significantly extend the sensitivity of terrestrial direct-detection experiments to sub-MeV dark-matter masses. We use a detailed Monte Carlo simulation to model the propagation and scattering of dark-matter particles in the Sun, including thermal effects, with special emphasis on ultralight dark-photon mediators. We study the properties of the SRDM flux, obtain exclusion limits from various direct-detection experiments, and provide projections for future experiments, focusing especially on those with silicon and xenon targets. We find that proposed future experiments with xenon and silicon targets can probe the entire “freeze-in benchmark”, in which dark matter is coupled to an ultralight dark photon, including dark-matter masses as low as 𝒪(keV). Our simulations and SRDM fluxes are publicly available.

Astronomy & Astrophysics↗
DOE OSTI2024

Dark matter induced baryonic feedback in galaxies

We demonstrate that nongravitational interactions between dark matter and baryonic matter can affect structural properties of galaxies. Detailed galaxy simulations and analytic estimates demonstrate that dark matter which collects inside white dwarf stars and ignites type Ia supernovae can substantially alter star formation, stellar feedback, and the halo density profile through a dark matter induced baryonic feedback process, distinct from usual supernova feedback in galaxies.

Formation & evolution of stars & galaxies↗
DOE OSTI2022

Galaxy–halo size relation from Sloan Digital Sky Survey Data Release 7 and the ELUCID simulation

ABSTRACT Based on galaxies in the Sloan Digital Sky Survey Data Release 7 and dark matter haloes in the dark matter only, cosmological, and constrained ELUCID simulation, we investigate the relation between the observed radii of central galaxies with stellar mass $\gtrsim\!{10}^{8} \, h^{-2}\, {\rm M}_\odot$ and the virial radii of their host dark matter haloes with virial mass $\gtrsim\!{10}^{10.5} \, h^{-1}\, {\rm M}_\odot$, and the dependence of galaxy–halo size relation on the halo spin and concentration. Galaxies in observation are matched to dark matter (sub)haloes in the ELUCID simulation using a novel neighbourhood subhalo abundance matching method. For galaxy two-dimensional (2D) half-light radii R50, we find that early- and late-type galaxies have the same power-law index 0.55 with $R_{50} \propto R_{\rm vir}^{0.55}$, although early-type galaxies have smaller 2D half-light radii than late-type galaxies at fixed halo virial radii. When converting the 2D half-light radii R50 to 3D half-mass radii r1/2, both early- and late-type galaxies display similar galaxy–halo size relations with $\log r_{1/2} = 0.55 \log (R_{\rm vir}/210 \, h^{-1}\, {\rm kpc}) + 0.39$. We find that the galaxy–halo size ratio r1/2/Rvir decreases with increasing halo mass. At fixed halo mass, there is no significant dependence of galaxy–halo size ratio on the halo spin or concentration.

Astronomy & Astrophysics↗
DOE OSTI2021

Velocity-dependent J-factors for annihilation radiation from cosmological simulations

Abstract We determine the dark matter pair-wise relative velocity distribution in a set of Milky Way-like halos in the Auriga and APOSTLE simulations. Focusing on the smooth halo component, the relative velocity distribution is well-described by a Maxwell-Boltzmann distribution over nearly all radii in the halo. We explore the implications for velocity-dependent dark matter annihilation, focusing on four models which scale as different powers of the relative velocity: Sommerfeld, s-wave, p-wave, and d-wave models. We show that the J-factors scale as the moments of the relative velocity distribution, and that the halo-to-halo scatter is largest for d-wave, and smallest for Sommerfeld models. The J-factor is strongly correlated with the dark matter density in the halo, and is very weakly correlated with the velocity dispersion. This implies that if the dark matter density in the Milky Way can be robustly determined, one can accurately predict the dark matter annihilation signal, without the need to identify the dark matter velocity distribution in the Galaxy.

Astronomy & Astrophysics↗
DOE OSTI2021

Learning effective physical laws for generating cosmological hydrodynamics with Lagrangian deep learning

The goal of generative models is to learn the intricate relations between the data to create new simulated data, but current approaches fail in very high dimensions. When the true data-generating process is based on physical processes, these impose symmetries and constraints, and the generative model can be created by learning an effective description of the underlying physics, which enables scaling of the generative model to very high dimensions. In this work, we propose Lagrangian deep learning (LDL) for this purpose, applying it to learn outputs of cosmological hydrodynamical simulations. The model uses layers of Lagrangian displacements of particles describing the observables to learn the effective physical laws. The displacements are modeled as the gradient of an effective potential, which explicitly satisfies the translational and rotational invariance. The total number of learned parameters is only of order 10, and they can be viewed as effective theory parameters. Further, we combine N-body solver fast particle mesh (FastPM) with LDL and apply it to a wide range of cosmological outputs, from the dark matter to the stellar maps, gas density, and temperature. The computational cost of LDL is nearly four orders of magnitude lower than that of the full hydrodynamical simulations, yet it outperforms them at the same resolution. We achieve this with only of order 10 layers from the initial conditions to the final output, in contrast to typical cosmological simulations with thousands of time steps. This opens up the possibility of analyzing cosmological observations entirely within this framework, without the need for large dark-matter simulations.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

The Effect of Warm Dark Matter on Early Star Formation Histories of Massive Galaxies: Predictions from the CROC Simulations

Several massive (M * > 108 M ⊙ ), high-redshift (z = 8–10) galaxies have recently been discovered to contain stars with ages of several hundred million years, pushing the onset of star formation in these galaxies back to z ~ 15. The very existence of stars formed so early may serve as a test for cosmological models with suppressed small-scale power (and, hence, late formation of cosmic structure). We explore the ages of the oldest stars in numerical simulations from the Cosmic Reionization On Computers project with cold dark matter (CDM) and two warm dark matter (WDM) cosmologies with 3 and 6 keV particles. There are statistically significant differences of ~5 Myr between average stellar ages of massive galaxies in CDM and 3 keV WDM, while CDM and 6 keV WDM are statistically indistinguishable. Even this 5 Myr difference, however, is much less than current observational uncertainties on the stellar population properties of high-redshift galaxies. The age distributions of all galaxies in all cosmologies fail to produce a substantial Balmer break, although uncertainties in dust attenuation are a potentially significant factor. Finally, we assess the convergence of our simulation predictions and find that the systematic uncertainties on individual galaxy properties are comparable to the differences between cosmologies, suggesting these differences may not be numerically robust.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Self-interacting Dark Matter Interpretation of Crater II

Abstract The satellite galaxy Crater II of the Milky Way is extremely cold and exceptionally diffuse. These unusual properties are challenging to understand in the standard model of cold dark matter. We use controlled N -body simulations to investigate the formation of Crater II in self-interacting dark matter (SIDM), where dark matter particles can scatter and thermalize. Taking the orbit motivated by the measurements from Gaia Early Data Release 3, we show a strong self-interacting cross section per particle mass of 60 cm 2 g −1 is favored for Crater II. The simulated SIDM halo, with a 1 kpc core, leads to both a low stellar velocity dispersion and a large half-light radius for Crater II. These characteristics remain robust regardless of the initial stellar distribution.

Astronomy & Astrophysics↗
DOE OSTI2021

Search for Lightly Ionizing Particles in SuperCDMS and simulation of neutron backgrounds

The Super Cryogenic Dark Matter Search (SuperCDMS) is a direct-detection dark matter search experiment that primarily aims to search for Weakly Interacting Massive Particles (WIMPs) using state-of-the-art solid-state detection technology. During its operation at the Soudan underground laboratory, germanium detectors were operated with high bias voltage mode known as the CDMS low ionization threshold experiment (CDMSlite) to achieve below-keV thresholds. CDMSlite, for being able to measure small energy depositions in detectors, also provides sensitivity to Lightly Ionizing Particles (LIPs) with very small fractional charges. This thesis will discuss an analysis to search LIPs with the data acquired in CDMSlite mode. An important component for LIPs search is the expected energy-deposition distributions for LIPs falling on the CDMSlite detector. In this thesis, a simulation framework to calculate the energy-deposition distributions is developed. This thesis presents first direct-detection limits on the intensity of cosmogenic LIPs with electric charges smaller than e /(3 × 10 5 ) as well as the strongest limits for charges ≤ e /160, with a minimum intensity of 1.36 × 10 -7 cm -2 s -1 sr -1 at charge e /160.In any rare-event search experiment, understanding background is crucial. Neutrons capable of mimicking dark matter signals are a major background for any dark matter search experiment. A simulation study to estimate the neutron background for an India based dark matter search experiment at Jaduguda Underground Science Laboratory (JUSL) is performed. The experiment at JUSL will be the first phase of a proposed Dark matter search at India-based Neutrino Observatory (DINO). It will be a direct detection experiment with primary aims to search for WIMPs as dark matter candidates. In this thesis, we discuss the methodology of estimating neutron flux at JUSL and report the results. The total neutron flux reaching the laboratory above 1 MeV energy threshold is found to be 5.76(±0.69) × 10 -6 cm -2 s -1 . The impact of neutron background on the sensitivity of the experiment to detect dark matter at JUSL is also discussed. The thesis is organized as follows. Chapter 1 provides a brief introduction to the Lightly Ionizing Particle (LIPs). The analysis to search LIPs in SuperCDMS is briefly outlined in the chapter. This chapter also discusses the importance of neutron background estimates in a dark matter search experiment, more specifically, in the context of a proposed India-based dark matter search experiment at Jaduguda Underground Science Laboratory. In Chapter 2, the SuperCDMS experiment is introduced. In Chapter 3, the framework developed to perform simulations for Lightly Ionizing Particles is presented. In Chapter 4, the LIPs search analysis with the CDMSlite data and the results are discussed. In Chapter 5, the simulation of neutron background and the feasibility of dark-matter search at JUSL is discussed. Finally, conclusions from all the results discussed in this thesis are presented in Chapter 6.

Banik, Samir↗
DOE OSTI2024

Deep learning insights into cosmological structure formation

The evolution of linear initial conditions present in the early Universe into extended halos of dark matter at late times can be computed using cosmological simulations. However, a theoretical understanding of this complex process remains elusive; in particular, the role of anisotropic information in the initial conditions in establishing the final mass of dark matter halos remains a long-standing puzzle. Here, we build a deep learning framework to investigate this question. We train a three-dimensional convolutional neural network to predict the mass of dark matter halos from the initial conditions, and quantify in full generality the amounts of information in the isotropic and anisotropic aspects of the initial density field about final halo masses. We find that anisotropies add a small, albeit statistically significant amount of information over that contained within spherical averages of the density field about final halo mass. However, the overall scatter in the final mass predictions does not change qualitatively with this additional information, only decreasing from 0.9 dex to 0.7 dex. Given such a small improvement, our results demonstrate that isotropic aspects of the initial density field essentially saturate the relevant information about final halo mass. Therefore, instead of searching for information directly encoded in initial conditions anisotropies, a more promising route to accurate, fast halo mass predictions is to add approximate dynamical information based e.g. on perturbation theory. More broadly, our results indicate that deep learning frameworks can provide a powerful tool for extracting physical insight into cosmological structure formation. Published by the American Physical Society 2024

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Dissipative Dark Substructure: The Consequences of Atomic Dark Matter on Milky Way Analog Subhalos

Using cosmological hydrodynamical zoom-in simulations, we explore the properties of subhalos in Milky Way analogs that contain a subcomponent of atomic dark matter (ADM). ADM differs from cold dark matter (CDM) due to the presence of self-interactions that lead to energy dissipation, analogous to standard model baryons. This model can arise in dark sectors that are natural and theoretically motivated extensions to the standard model. The simulations used in this work were carried out using GIZMO and utilize the FIRE-2 galaxy formation physics in the standard model baryonic sector. For the parameter points we consider, the ADM gas cools efficiently, allowing it to collapse to the center of subhalos. This increases a subhalo's central density and affects its orbit, with more subhalos surviving small pericentric passages. The subset of subhalos that host satellite galaxies have cuspier density profiles and smaller stellar half-mass radii relative to CDM. The entire population of dwarf galaxies produced in the ADM simulations is more compact than those seen in CDM simulations, unable to reproduce the entire diversity of observed dwarf galaxy structures. Additionally, we also identify a population of highly compact subhalos that consist nearly entirely of ADM and form in the central region of the host, where they can leave distinctive imprints in the baryonic disk. This work presents the first detailed exploration of subhalo properties in a strongly dissipative dark matter scenario, providing intuition for how other regions of ADM parameter space, as well as other dark sector models, would impact galactic-scale observables.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

guppy i : a code for reducing the storage requirements of cosmological simulations

ABSTRACT As cosmological simulations have grown in size, the permanent storage requirements of their particle data have also grown. Even modest simulations present a major logistical challenge for the groups which run these boxes and researchers without access to high performance computing facilities often need to restrict their analysis to lower quality data. In this paper, we present guppy, a compression algorithm and code base tailored to reduce the sizes of dark matter-only cosmological simulations by approximately an order of magnitude. guppy is a ‘lossy’ algorithm, meaning that it injects a small amount of controlled and uncorrelated noise into particle properties. We perform extensive tests on the impact that this noise has on the internal structure of dark matter haloes, and identify conservative accuracy limits which ensure that compression has no practical impact on single-snapshot halo properties, profiles, and abundances. We also release functional prototype libraries in C, Python, and Go for reading and creating guppy data.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Clusters have edges: the projected phase-space structure of SDSS redMaPPer clusters

ABSTRACT We study the distribution of line-of-sight velocities of galaxies in the vicinity of Sloan Digital Sky Survey (SDSS) red-sequence Matched-filter Probabilistic Percolation (redMaPPer) galaxy clusters. Based on their velocities, galaxies can be split into two categories: galaxies that are dynamically associated with the cluster, and random line-of-sight projections. Both the fraction of galaxies associated with the galaxy clusters, and the velocity dispersion of the same, exhibit a sharp feature as a function of radius. The feature occurs at a radial scale Redge ≈ 2.2Rλ, where Rλ is the cluster radius assigned by redMaPPer. We refer to Redge as the ‘edge radius’. These results are naturally explained by a model that further splits the galaxies dynamically associated with a galaxy cluster into a component of galaxies orbiting the halo and an infalling galaxy component. The edge radius Redge constitutes a true ‘cluster edge’, in the sense that no orbiting structures exist past this radius. A companion paper tests whether the ‘halo edge’ hypothesis holds when investigating the full three-dimensional phase-space distribution of dark matter substructures in numerical simulations, and demonstrates that this radius coincides with a suitably defined splashback radius.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

QUOTAS: A New Research Platform for the Data-driven Discovery of Black Holes

We present QUOTAS, a novel research platform for the data-driven investigation of supermassive black hole (SMBH) populations. While SMBH data—observations and simulations—have grown in complexity and abundance, our computational environments and tools have not matured commensurately to exhaust opportunities for discovery. To explore the BH, host galaxy, and parent dark matter halo connection—in this pilot version—we assemble and colocate the high-redshift, z > 3 quasar population alongside simulated data at the same cosmic epochs. As a first demonstration of the utility of QUOTAS, we investigate correlations between observed Sloan Digital Sky Survey (SDSS) quasars and their hosts with those derived from simulations. Leveraging machine-learning algorithms (ML), to expand simulation volumes, we show that halo properties extracted from smaller dark-matter-only simulation boxes successfully replicate halo populations in larger boxes. Next, using the Illustris-TNG300 simulation that includes baryonic physics as the training set, we populate the larger LEGACY Expanse dark-matter-only box with quasars, and show that observed SDSS quasar occupation statistics are accurately replicated. First science results from QUOTAS comparing colocated observational and ML-trained simulated data at z3 are presented. QUOTAS demonstrates the power of ML, in analyzing and exploring large data sets, while also offering a unique opportunity to interrogate theoretical assumptions that underpin accretion and feedback models. QUOTAS and all related materials are publicly available at the Google Kaggle platform. (The full data set—observational data and simulation data—are available at: https://www.kaggle.com/ and the codes are available at:https://www.kaggle.com/datasets/quotasplatform/quotas)

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

UniverseMachine: Predicting Galaxy Star Formation over Seven Decades of Halo Mass with Zoom-in Simulations

In this work, we apply the empirical galaxy–halo connection model UniverseMachine to dark-matter-only zoom-in simulations of isolated Milky Way (MW)–mass halos, along with their parent cosmological simulations. This application extends UniverseMachine predictions into the ultrafaint dwarf galaxy regime (10 2 M ⊙ ≤ M * ≤ 10 5 M ⊙) and yields a well-resolved stellar mass–halo mass (SMHM) relation over the peak halo mass range of 10 8 –10 15 M ⊙. The extensive dynamic range provided by the zoom-in simulations allows us to assess specific aspects of dwarf galaxy evolution predicted by UniverseMachine. In particular, although UniverseMachine is not constrained for dwarf galaxies with M * ≲ 10 8 M ⊙, our predicted SMHM relation is consistent with that inferred for MW satellite galaxies at z = 0 using abundance matching. However, UniverseMachine predicts that nearly all galaxies are actively star-forming below M * ~ 10 7 M ⊙ and that these systems typically form more than half of their stars at z ≲ 4, which is discrepant with the star formation histories of Local Group dwarf galaxies that favor early quenching.

79 ASTRONOMY AND ASTROPHYSICS↗